CRAN Package Check Results for Maintainer ‘Sebastian Hönel <sebastian.honel at lnu.se>’

Last updated on 2025-12-28 03:52:17 CET.

Package	ERROR	NOTE	OK
mmb	2	5	6

Package mmb

Current CRAN status: ERROR: 2, NOTE: 5, OK: 6

Version: 0.13.3
Check: CRAN incoming feasibility
Result: NOTE Maintainer: ‘Sebastian Hönel <sebastian.honel@lnu.se>’ No Authors@R field in DESCRIPTION. Please add one, modifying Authors@R: person(given = "Sebastian", family = "Hönel", role = c("aut", "cre"), email = "sebastian.honel@lnu.se") as necessary. Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc

Version: 0.13.3
Check: examples
Result: ERROR Running examples in ‘mmb-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: bayesProbabilityAssign > ### Title: Assign probabilities to one or more samples, given some training > ### data. > ### Aliases: bayesProbabilityAssign > ### Keywords: classification full-dependency inferencing > > ### ** Examples > > w <- mmb::getWarnings() > mmb::setWarnings(FALSE) [1] FALSE > > set.seed(84735) > rn <- base::sample(rownames(iris), 150) > dfTrain <- iris[rn[1:120], ] > dfValid <- iris[rn[121:150], !(colnames(iris) %in% "Species") ] > mmb::bayesProbabilityAssign(dfTrain, dfValid, "Species") Error in xtfrm.data.frame(list(virginica = 0.0475794229174146, versicolor = 0.0513857767508078, : cannot xtfrm data frames Calls: <Anonymous> -> xtfrm -> xtfrm.data.frame Execution halted Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc

Version: 0.13.3
Check: tests
Result: ERROR Running ‘helpers.R’ [0s/1s] Running ‘testthat.R’ [36s/52s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(mmb) > > test_check("mmb") Saving _problems/test_bayes-346.R Saving _problems/test_bayes-429.R Saving _problems/test_bayes-462.R Saving _problems/test_bayesRegress-40.R Saving _problems/test_bayesRegress-57.R Saving _problems/test_bayesRegress-122.R Saving _problems/test_discretization-68.R Saving _problems/test_pdfAndProb-13.R Saving _problems/test_pdfAndProb-21.R Saving _problems/test_warnings-16.R [ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_bayes.R:343:3'): the full Bayesian works with many variables ─── Error in `xtfrm.data.frame(structure(list(`4` = 0, `8` = 0, `6` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:343:3 2. ├─base::xtfrm(`<df[,3]>`) 3. └─base::xtfrm.data.frame(`<df[,3]>`) ── Error ('test_bayes.R:427:3'): assigning for multiple works using naive Bayes ── Error in `xtfrm.data.frame(structure(list(virginica = 0.000578947368421053, versicolor = 0.000966428571428572, setosa = 0.2728171875), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:427:3 2. ├─base::xtfrm(`<df[,3]>`) 3. └─base::xtfrm.data.frame(`<df[,3]>`) ── Error ('test_bayes.R:460:3'): we can do online learning and return factors ── Error in `xtfrm.data.frame(structure(list(setosa = 0.0133000875267292, versicolor = 0.0722285917992075, virginica = 2.60391628278781), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:460:3 2. ├─base::xtfrm(`<df[,3]>`) 3. └─base::xtfrm.data.frame(`<df[,3]>`) ── Error ('test_bayesRegress.R:36:5'): we can also sample from the most likely range only ── Error in `xtfrm.data.frame(structure(list(rowname = "1", `1` = 0.51, `2` = 0.18, `3` = 0.11, `6` = 0.27, `5` = 0.31, `7` = 0.15, `4` = 0.17), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. ├─testthat::expect_warning(...) at test_bayesRegress.R:35:3 2. │ └─testthat:::quasi_capture(...) 3. │ ├─testthat (local) .capture(...) 4. │ │ └─base::withCallingHandlers(...) 5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 6. └─mmb::bayesRegress(...) at test_bayesRegress.R:36:5 7. ├─base::xtfrm(`<df[,8]>`) 8. └─base::xtfrm.data.frame(`<df[,8]>`) ── Error ('test_bayesRegress.R:53:5'): custom regressor errors are handled properly ── Error in `xtfrm.data.frame(structure(list(rowname = "1", `3` = 1.1, `1` = 0, `2` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. ├─testthat::expect_warning(...) at test_bayesRegress.R:52:3 2. │ └─testthat:::quasi_capture(...) 3. │ ├─testthat (local) .capture(...) 4. │ │ └─base::withCallingHandlers(...) 5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 6. └─mmb::bayesRegress(...) at test_bayesRegress.R:53:5 7. ├─base::xtfrm(`<df[,4]>`) 8. └─base::xtfrm.data.frame(`<df[,4]>`) ── Error ('test_bayesRegress.R:120:3'): regression for multiple values works in simple and online, too ── Error in `xtfrm.data.frame(structure(list(rowname = "1", `2` = 0.186029411764706, `1` = 0.071875, `3` = 0.167013888888889, `4` = 0.00379322681452557, `6` = 0.00570421505598071, `5` = 1.49004290740905, `7` = 0.174182093347807), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesRegressAssign(...) at test_bayesRegress.R:120:3 2. └─mmb::bayesRegress(...) 3. ├─base::xtfrm(`<df[,8]>`) 4. └─base::xtfrm.data.frame(`<df[,8]>`) ── Failure ('test_discretization.R:68:3'): numRanges is not required ─────────── Expected `discretizeVariableToRanges(c(1))` to produce warnings. ── Failure ('test_pdfAndProb.R:11:3'): estimation for small data works ───────── Expected `{ ... }` to produce warnings. ── Failure ('test_pdfAndProb.R:19:3'): estimation for small data works ───────── Expected `{ ... }` to produce warnings. ── Failure ('test_warnings.R:16:3'): en-/disabling warnings/errors works ─────── Expected `mmb::getWarnings()` to be TRUE. Differences: `actual`: FALSE `expected`: TRUE [ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.13.3
Check: tests
Result: ERROR Running ‘helpers.R’ [0s/0s] Running ‘testthat.R’ [22s/28s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > library(testthat) > library(mmb) > > test_check("mmb") Saving _problems/test_bayes-346.R Saving _problems/test_bayes-429.R Saving _problems/test_bayes-462.R Saving _problems/test_bayesRegress-40.R Saving _problems/test_bayesRegress-57.R Saving _problems/test_bayesRegress-122.R Saving _problems/test_discretization-68.R Saving _problems/test_pdfAndProb-13.R Saving _problems/test_pdfAndProb-21.R Saving _problems/test_warnings-16.R [ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_bayes.R:343:3'): the full Bayesian works with many variables ─── Error in `xtfrm.data.frame(structure(list(`4` = 0, `8` = 0, `6` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:343:3 2. ├─base::xtfrm(`<df[,3]>`) 3. └─base::xtfrm.data.frame(`<df[,3]>`) ── Error ('test_bayes.R:427:3'): assigning for multiple works using naive Bayes ── Error in `xtfrm.data.frame(structure(list(virginica = 0.000578947368421053, versicolor = 0.000966428571428572, setosa = 0.2728171875), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:427:3 2. ├─base::xtfrm(`<df[,3]>`) 3. └─base::xtfrm.data.frame(`<df[,3]>`) ── Error ('test_bayes.R:460:3'): we can do online learning and return factors ── Error in `xtfrm.data.frame(structure(list(setosa = 0.0133000875267292, versicolor = 0.0722285917992075, virginica = 2.60391628278781), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:460:3 2. ├─base::xtfrm(`<df[,3]>`) 3. └─base::xtfrm.data.frame(`<df[,3]>`) ── Error ('test_bayesRegress.R:36:5'): we can also sample from the most likely range only ── Error in `xtfrm.data.frame(structure(list(rowname = "1", `1` = 0.51, `2` = 0.18, `3` = 0.11, `6` = 0.27, `5` = 0.31, `7` = 0.15, `4` = 0.17), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. ├─testthat::expect_warning(...) at test_bayesRegress.R:35:3 2. │ └─testthat:::quasi_capture(...) 3. │ ├─testthat (local) .capture(...) 4. │ │ └─base::withCallingHandlers(...) 5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 6. └─mmb::bayesRegress(...) at test_bayesRegress.R:36:5 7. ├─base::xtfrm(`<df[,8]>`) 8. └─base::xtfrm.data.frame(`<df[,8]>`) ── Error ('test_bayesRegress.R:53:5'): custom regressor errors are handled properly ── Error in `xtfrm.data.frame(structure(list(rowname = "1", `3` = 1.1, `1` = 0, `2` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. ├─testthat::expect_warning(...) at test_bayesRegress.R:52:3 2. │ └─testthat:::quasi_capture(...) 3. │ ├─testthat (local) .capture(...) 4. │ │ └─base::withCallingHandlers(...) 5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo)) 6. └─mmb::bayesRegress(...) at test_bayesRegress.R:53:5 7. ├─base::xtfrm(`<df[,4]>`) 8. └─base::xtfrm.data.frame(`<df[,4]>`) ── Error ('test_bayesRegress.R:120:3'): regression for multiple values works in simple and online, too ── Error in `xtfrm.data.frame(structure(list(rowname = "1", `2` = 0.186029411764706, `1` = 0.071875, `3` = 0.167013888888889, `4` = 0.00379322681452557, `6` = 0.00570421505598071, `5` = 1.49004290740905, `7` = 0.174182093347807), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames Backtrace: ▆ 1. └─mmb::bayesRegressAssign(...) at test_bayesRegress.R:120:3 2. └─mmb::bayesRegress(...) 3. ├─base::xtfrm(`<df[,8]>`) 4. └─base::xtfrm.data.frame(`<df[,8]>`) ── Failure ('test_discretization.R:68:3'): numRanges is not required ─────────── Expected `discretizeVariableToRanges(c(1))` to produce warnings. ── Failure ('test_pdfAndProb.R:11:3'): estimation for small data works ───────── Expected `{ ... }` to produce warnings. ── Failure ('test_pdfAndProb.R:19:3'): estimation for small data works ───────── Expected `{ ... }` to produce warnings. ── Failure ('test_warnings.R:16:3'): en-/disabling warnings/errors works ─────── Expected `mmb::getWarnings()` to be TRUE. Differences: `actual`: FALSE `expected`: TRUE [ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.13.3
Check: dependencies in R code
Result: NOTE Namespaces in Imports field not imported from: ‘datasets’ ‘doParallel’ ‘parallel’ All declared Imports should be used. Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.13.3
Check: LazyData
Result: NOTE 'LazyData' is specified without a 'data' directory Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64